RegCovid19: A collaborative software to help against SARS-CoV-2 virus

Autor: Zubizarreta, Ion, Arruti, Egoitz, Pérez-Asenjo, Javier
Rok vydání: 2022
Předmět:
Zdroj: International Journal of Integrated Care; Vol 22: Annual Conference Supplement 2022; 39
ISSN: 1568-4156
Popis: The outbreak of Coronavirus disease (COVID-19) in 2019, caused by the virus coronavirus 2 (SARS-CoV-2), has so far killed more than 4.500.000 and infected more than 225 million people around the world. This new disease, which was unknown to the medical community, collapsed the Spanish health system in 2020. The lack of coordination and information transfer was one of the great challenges faced by the medical community. Therefore, to help on these challenges, in April 2020, Ubikare decided to develop an E-health record system and make it available to hospitals for free.This collaborative software tool, called RegCovid19 and endorsed by the Spanish Society of Anaesthesiology and Resuscitation (SEDAR), was designed by medical professionals for use both in hospitalization and in ICUs. The goal was to improve the information management (allowing the automatic and homogeneous collection of information), the collaboration between hospitals (sharing the information openly and in real-time with the rest of hospitals) and to learn different ways to fight the disease of Covid-19 pandemic.One important property of RegCovid19 is provide to healthcare personnel a simple and efficient view of the evolution and situation of each patient, with their corresponding severity scales. This way, the obtained information on the initial stages and the course of the disease, as well as the evolution of the applied treatments, allowed the medical community to understand better the factors associated with the illness and to optimize existing resources. More than 35 hospitals in Spain and Andorra participated on RegCovid19 by contributing and sharing the information of more than 11 thousand patients admitted in their hospitals.RegCovid19 software has embedded a data analytics component, to process information in real time. This module allows to analize every new input data, and obtains new output based on the hypothesis introduced by researchers. All this information was reported every day to data analysts thanks to the automatic export module. This way, new conclusions or fresh hypothesis were obtained every day to learn how the disease was affecting to the population. This iterative way of working, made possible to have a high impact publications faster than a traditional research method on medicine, were the conclusions are obtained at the end of the research. Proof of this work are the 5 publications about different treatments against SARS-CoV-2.RegCovid19 was possible thanks to the cooperation of different agents who intervened in the process like hospitals, healthcare professionals, clinics, engineers, etc. It's a clear collaboration project, where the contribution of multidisciplinary profiles as engineers, doctors and data analysts were key to the success of the project and to combat the disease.
Databáze: OpenAIRE